%0 Journal Article %1 bonten_understanding_2001 %A Bonten, M J %A Austin, D J %A Lipsitch, M %D 2001 %J Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America %K Agents, Bacteria, Bacterial Bacterial, Biological Control, Cross Drug Hospitals, Humans, Infection Infection, Infections, Mathematics, Models, Resistance, {Anti-Bacterial} %N 10 %P 1739--46 %R 11595995 %T Understanding the spread of antibiotic resistant pathogens in hospitals: mathematical models as tools for control %U http://www.ncbi.nlm.nih.gov/pubmed/11595995 %V 33 %X As microorganisms become more resistant to antimicrobial agents, effective infection control measures will become increasingly important. However, despite multiple studies on infection prevention, few data exist on the quantitative effects of the individual aspects of infection control strategies. The combination of epidemiologic surveillance, molecular genotyping, observational studies on compliance, and mathematical modeling may improve our ability to determine the quantitative effects of individual infection control measures. This may help to design more effective infection control programs. In this study, we review several of the models that have been published and speculate on the usefulness of mathematical modeling for improving the prevention of infection.

@article{bonten_understanding_2001, abstract = {As microorganisms become more resistant to antimicrobial agents, effective infection control measures will become increasingly important. However, despite multiple studies on infection prevention, few data exist on the quantitative effects of the individual aspects of infection control strategies. The combination of epidemiologic surveillance, molecular genotyping, observational studies on compliance, and mathematical modeling may improve our ability to determine the quantitative effects of individual infection control measures. This may help to design more effective infection control programs. In this study, we review several of the models that have been published and speculate on the usefulness of mathematical modeling for improving the prevention of infection.}, added-at = {2011-03-11T10:05:34.000+0100}, author = {Bonten, M J and Austin, D J and Lipsitch, M}, biburl = {https://www.bibsonomy.org/bibtex/2e97fa7861f0e7831a28716e83f98a47a/jelias}, doi = {11595995}, interhash = {d40d5c7d85e5830d36e30ce174525931}, intrahash = {e97fa7861f0e7831a28716e83f98a47a}, issn = {1058-4838}, journal = {Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America}, keywords = {Agents, Bacteria, Bacterial Bacterial, Biological Control, Cross Drug Hospitals, Humans, Infection Infection, Infections, Mathematics, Models, Resistance, {Anti-Bacterial}}, month = nov, note = {{PMID:} 11595995}, number = 10, pages = {1739--46}, shorttitle = {Understanding the spread of antibiotic resistant pathogens in hospitals}, timestamp = {2011-03-11T10:06:41.000+0100}, title = {Understanding the spread of antibiotic resistant pathogens in hospitals: mathematical models as tools for control}, url = {http://www.ncbi.nlm.nih.gov/pubmed/11595995}, volume = 33, year = 2001 }